| Project/Area Number |
21500284
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | Doshisha University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
HATANO Kenji 同志社大学, 文化情報学部, 准教授 (80314532)
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2009: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | クラスター分析 / 多次元尺度構成法 / シンボリックデータ / 大規模複雑データ / 類似性データ / 大量複雑データ / クラスター分析法 / 多次元尺度構構成法 / シンボリリックデータ |
|---|
| Research Abstract |
In this study, we categorized various types of existing methods for relational data and proposed new methods for analysis of the data and evaluation of the results. As a main result, new methods for multidimensional scaling, clustering algorithm and network analysis have been proposed to deal with the large and complex data. More precisely, the large and complex data are regarded as symbolic data, which consists of multi-valued data, interval-valued data and distribution-valued data, and several methods that reduce the loss of information have been proposed based on the notion of symbolic data.
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